Stock purchase indices

ABSTRACT

A method and system for determining investor participation driven stock purchase indices. Raw customer trading data is received from an accounting system. The raw customer trading data is then aggregated to generate daily transaction total counts for all stocks (that is, total shares bought and sold, total market value, etc.) as well as daily transaction total counts for each individual stock. Aggregation of the raw customer data also addresses customer privacy concerns. The aggregated data is processed to produce moving averages, stock purchase indices, and stock rankings. The stock purchase indices are based on a diffusion index technique of segregating buyers from sellers, and with these relative counts, measures the breadth of investor purchasing participation. The stock purchase indices are then displayed to a graphical user interface. The display includes stock buy and sell ranking lists.

This application is a divisional of U.S. application Ser. No.09/414,781, filed Oct. 8, 1999 now U.S. Pat. No. 6,901,383 (incorporatedby reference herein in its entirety), which claims the benefit under 35U.S.C. §119(e) of U.S. Provisional Application No. 60/135,143, filed May20, 1999 (incorporated by reference herein in its entirety).

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates to the field of information processing.More particularly, the present invention is a system and method thatgenerates a diffusion index for measuring the breadth of individualinvestor participation in the stock market.

2. Related Art

An index is a statistical composite that is used to indicate theperformance of a market or a market sector over various time periods.Examples of indices that are used to gauge the performance of stocks andother securities in the United States include the Dow Jones IndustrialAverage, the National Association of Securities Dealers AutomatedQuotations (NASDAQ) Composite Index, the New York Stock ExchangeComposite Index, etc. In general, the Dow Jones Industrial Averagecontains thirty (30) stocks that trade on the New York Stock Exchangeand is a general indicator of how shares of the largest United Statescompanies are trading. The NASDAQ Composite Index is a composite indexof more than three thousand (3,000) companies listed on the NASDAQ (alsoreferred to as over-the-counter or OTC stocks). It is designed toindicate the stock performance of small-cap and technology stocks.Finally, the New York Stock Exchange Composite Index is a compositeindex of shares listed on the New York Stock Exchange.

All of the above-listed stock market indices are related to changes inthe price of the securities included in the particular index. What isneeded is an economic indicator that measures investor confidence andparticipation in buying stocks rather than the value of stocks and whichstocks are being traded. What is further needed is an indicator thatfocuses on how the participation rate of investors varies over time.

SUMMARY OF THE INVENTION

The present invention satisfies the above-mentioned needs by providing amethod and system for determining investor participation drivensecurities trades indices, generally known as stock purchase indices.Raw customer trading data is received from an accounting system. The rawcustomer trading data is then aggregated to generate daily transactiontotal counts for all stocks (that is, total shares bought and sold,total market value, etc.) as well as daily transaction total counts foreach individual stock. Aggregation of the raw customer data alsoaddresses customer privacy concerns. The aggregated data is processed toproduce moving averages, stock purchase indices, and stock rankings. Thestock purchase indices are based on a diffusion index technique ofsegregating buyers from sellers, and with these relative counts, measureinvestor purchasing participation. The stock purchase indices are thendisplayed to a graphical user interface. The display includes stock buyand sell ranking lists.

The stock purchase indices of the present invention include a buy simpleindex, a sell simple index, a buy weighted index, and a sell weightedindex.

Further features and advantages of the invention, as well as thestructure and operation of various embodiments of the invention, aredescribed in detail below with reference to the accompanying drawings.

BRIEF DESCRIPTION OF THE FIGURES

The features, objects, and advantages of the present invention willbecome more apparent from the detailed description set forth below whentaken in conjunction with the drawings in which like referencecharacters identify corresponding elements throughout. In the drawings,like reference numbers generally indicate identical, functionallysimilar, and/or structurally similar elements. The drawings in which anelement first appears is indicated by the leftmost digit(s) in thecorresponding reference number.

FIG. 1 is a data flow diagram illustrating the process for determiningstock purchase indices of the present invention.

FIG. 2 is a high level flow chart illustrating a method for determiningthe stock purchase indices of the present invention.

FIG. 3 is a diagram illustrating an architectural overview of a stockpurchase index system of the present invention.

FIG. 4 is a diagram illustrating an exemplary back office accountingdatabase.

FIG. 5 is a diagram illustrating an exemplary total and stock countdatabase.

FIG. 6 is a diagram illustrating an exemplary moving index database.

FIGS. 7A and 7B are diagrams illustrating an exemplary stock rankingdatabase.

FIG. 8 is a diagram illustrating an exemplary embodiment of anaggregator.

FIG. 9 is a flow diagram for determining a simple buy index.

FIGS. 10A and 10B are flow diagrams for determining a weighted buyindex.

FIG. 11 is a flow diagram for determining stock ranking.

FIGS. 12A, 12B, and 12C are diagrams illustrating an example of how thebuy simple index and sell simple index are determined.

FIG. 13 represents a formula for determining moving index averages.

FIG. 14 is a flow diagram for determining moving index averages.

FIG. 15 is a diagram illustrating an example of how a moving indexaverage is determined.

FIG. 16A is a diagram illustrating a standard daily default email reportof the simple buy index.

FIG. 16B is a diagram illustrating a standard weekly default emailreport of the simple buy index.

FIG. 17 is a diagram illustrating a graphical representation of thesimple buy index as seen by a user logging onto the services web site.

FIG. 18 is a diagram illustrating the application of a filter to selecta daily or weekly series.

FIG. 19 is a diagram illustrating the application of a filter to selectdifferent smoothing period lengths.

FIG. 20 is a diagram illustrating the application of a filter to selectdifferent smoothing period lengths for the comparison series.

FIG. 21 is a diagram illustrating the application of a filter to selectan ending date for period-to-period change reporting and stock listings.

FIG. 22 is a diagram illustrating the application of a filter thatallows the length of time covered by the change measurements to bealtered.

FIG. 23 is a diagram illustrating the application of a filter forchanging the number of stocks listed in the top stock buys and sellslists.

FIG. 24 is a diagram illustrating the application of a filter thatallows the first stock listing selections to be changed.

FIG. 25 is a diagram illustrating the application of a filter forallowing the second stock listing selections to be changed.

FIG. 26 is a diagram illustrating the application of a filter forallowing the first stock ranking selection criteria to be changed.

FIG. 27 is a diagram illustrating the application of a filter thatenables the second stock ranking selection criteria to be changed.

FIGS. 28A and 28B are diagrams illustrating the application of a filterfor enabling all of the underlying stocks included in the index to bechanged.

FIGS. 29A and 29B are diagrams illustrating the addition of a comparisonindices graph for comparing the simple buy index to a comparative index.

FIG. 30 is a diagram illustrating the application of a filter thatenables a displayed comparative index to be altered by allowing theselection of weekly or daily series and moving average smoothing periodsfor the comparative index selection.

FIG. 31 is a diagram illustrating an exemplary alert setting based onchanges from the prior period.

FIG. 32 is a diagram illustrating an exemplary alert setting based onmeasurements of the gap.

FIG. 33 is a diagram illustrating an exemplary computer system.

FIG. 34 is a diagram illustrating an exemplary other index database.

FIG. 35 is a diagram illustrating exemplary types of records found in areporting controls database.

FIG. 36 is a diagram illustrating exemplary stock description data foundin the reporting controls database.

FIGS. 37A and 37B show a diagram illustrating exemplary filter controlsdata found in the reporting controls database.

FIG. 38 is a diagram illustrating exemplary alert controls data found inthe reporting controls database.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Table of Contents

-   I. Overview of The Present Invention-   II. Databases of The Present Invention    -   A. Back Office System (BOS) Database    -   B. Total and Stock Counts Database    -   C. Periods Moving Index Database    -   D. Periods Stock Ranking Database    -   E. Other Index Database    -   F. Reporting Controls Database-   III. General System Operation    -   A. Aggregator: Creation of Total and Stock Counts Database    -   B. Moving Average Generator: Creation of Buy Simple Index and        Sell Simple Index    -   C. Moving Average Generator: Creation of Buy Simple Rank, Sell        Simple Rank, Buy Weighted Index and Sell Weighted Index    -   D. Moving Average Generator: Creation of Buy Weighted Rank and        Sell Weighted Rank    -   E. Smoothing Techniques    -   F. Time Series Analysis-   IV. Graphical User Interface-   V. Environment-   VI. Conclusion

I. Overview of The Present Invention

While the present invention is described herein with reference toillustrative embodiments for particular applications, it should beunderstood that the invention is not limited thereto. Those skilled inthe art with access to the teachings provided herein will recognizeadditional modifications, applications, and embodiments within the scopethereof and additional fields in which the present invention would be ofsignificant utility.

The present invention is directed towards a system and method forproviding securities trades indices, generally known as stock purchaseindices, based on investor participation. The stock purchase indicesmeasure the participation rates of who is buying and selling stocksrather than the value of what is being bought or sold. The method ofconstruction combines economic analysis with technical stock marketanalysis techniques. The present invention is a tool for identifyingperiods when investors are exhibiting confidence in the economy andidentifying companies in which investor confidence is being demonstratedby the purchase of their stocks. This is especially important in timesof general economic uncertainty, unfavorable national and internationalnews, and falling stock prices.

The stock purchase indices of the present invention are based on adiffusion index model that measures investor purchasing participation.The stock purchase indices of the present invention measure whatpercentage of customers are meeting a selected criteria of executing abuy order versus a sell order.

FIG. 1 is a data flow diagram 100 illustrating the process fordetermining the stock purchase indices of the present invention. Dataflow diagram 100 comprises a back office accounting system (BOS) 102, anaggregator 104, a moving average generator 108, a user interfacedelivery module 116, and a plurality of databases 106, 110, 112, 114,and 122. Data flow diagram 100 also comprises stock purchase reports inthe form of email 118 and web site 120 delivery.

BOS 102 contains customer records for investor transactions andholdings. BOS 102 is used to generate trade confirmations, monthlystatements, and to satisfy government reporting requirements. Rawcustomer data is extracted from BOS 102 and sent to aggregator 104.

Aggregator 104 extracts and summarizes the raw customer data to obtaindaily transaction total counts for all stocks bought and sold (that is,total number of accounts and orders, total number of shares bought andsold, total market value, etc.) and daily transaction counts for eachindividual stock bought and sold for determining stock purchase indices.Aggregator 104 also acts as a protective shield to address the privacyconcerns of the customers. A more detailed description of aggregator 104is described below with reference to FIG. 8. Database 106 is used tostore each day's transaction total counts and individual stock countsdata generated by aggregator 104.

In a preferred embodiment, moving average generator 108 extracts thetransaction total counts and individual stock counts data from database106 and determines the moving averages, the stock purchase indices, andthe stock rankings for periods 1, 5, 9, and 21. Period time frames aretypically daily or weekly. However, the present invention is not limitedto periods of 1, 5, 9, and 21 and period time frames of daily andweekly. One skilled in the relevant art(s) would know that other periodsand period time frames could be used without departing from the scopeand spirit of the present invention.

The present invention involves the analysis of recurring and periodicvariations in time series data relating to buyer and seller purchasing.Time series data includes trends, cycles, seasonal, and irregularcomponents. The present invention removes the irregular and seasonalcomponents from the time series data in order to obtain a clear measureof the trends and cycle variations in buyer and seller purchases. Theirregular component of time series data is referred to as “noise.” Thenoise component of the data is removed by applying smoothing techniques,such as moving averages. Moving averages are averages of the data overperiods of time. The seasonal component of time series data refers todata that exhibits a recurring variation, up or down, which occurs thesame time each year. An example of seasonal time series data is aretirement account. In one embodiment of the present invention,retirement accounts are excluded because of suspected seasonalityrelated to filing deadlines. In an alternative embodiment, retirementaccounts are included by using the U.S. Census Bureau's X11 procedure totreat and remove the seasonality component from the data. The U.S.Census Bureau's X11 procedure incorporates a ratio to moving averageapproach, which is described in Business Cycles and Forecasting, byCarl. A. Dauten and Lloyd M. Valentine, Southwestern Publishing Co., pp.235-240 (1978), which is incorporated by reference herein in itsentirety.

The stock purchase indices of the present invention are a measure ofinvestor participation in the stock market. These stock purchase indicesinclude a buy simple index, a sell simple index, a buy weighted index,and a sell weighted index. The buy simple index is a measure of theratio of investors that bought stocks over a period of time to the totalinvestors that bought or sold stocks within that period. The sell simpleindex is a measure of the ratio of investors that sold stocks over aperiod of time to the total investors that bought or sold stocks withinthat period. Weighted indices are used to discount the value of smallvalue transactions. For example, weighting reduces the economic impactof the relatively small value of the purchase of a “penny stock.” Thebuy weighted index is a measure of the ratio of investors that boughtstocks over a period of time to the total investors that bought or soldstocks within that period, weighted by the cost of the transactions. Thesell weighted index is a measure of the ratio of investors that soldstocks over a period of time to the total investors that bought or soldstocks within that period, weighted by the cost of the transactions.Although the stock purchase indices of the present invention aredirected to the number of customer executions of buy and selltransactions, the present invention is not limited to this. Otherindices can be generated, such as an index relating to the number ofshares bought to the total number of shares bought and sold, the numberof buy orders to the total number of buy and sell orders, or the dollarvalue of all buy trades to the dollar value of all buy and sell trades,etc., without departing from the scope and spirit of the invention.

Stock rankings are based on the stock purchase indices of the presentinvention. Stock rankings comprise a list of the top stocks bought and alist of the top stocks sold over a given period of time. Each listincludes each stock's percentage of the total number of stocks bought orthe total number of stocks sold, respectively.

Database 110 stores the results of the stock purchase indices as well asthe 1, 5, 9, and 21 period moving average indices data. Database 112stores the results of the 1, 5, 9, and 21 period stock ranking data.

User interface delivery module 116 extracts the moving index data andstock ranking data from databases 110 and 112, respectively, for displaypurposes. Users can request that a stock purchase index report bedelivered via email 118. Alternatively, a user may log onto web site 120for the service providing the stock purchase index to obtain a stockpurchase index report. When the user obtains the stock purchase index bylogging onto web site 120, additional options are available to the user.Such options include, but are not limited to, viewing the data inconjunction with other indices, filtering the data to allow the user toselect the results based on business sector, exchange, period,capitalization, country, and different customer investment profilesegments, etc. Other indices data are stored in database 114. Additionaloptions include providing user-defined alerts for enabling an automaticemail 118 delivery when certain criteria are met, such as a percentchange in the stock purchase index from the prior period or a percentchange in gap. Gap refers to the difference between a base period seriesand a comparison period series. In a preferred embodiment of the presentinvention, the base period series is usually 9 days or 9 weeks and thecomparison period series is usually 21 days or 21 weeks, respectively.Selected filters and alerts are stored in reporting controls database122.

A high level flow chart 200 illustrating a method for determining thestock purchase index of the present invention is shown in FIG. 2. Theprocess begins with step 202 where control is passed to step 204.

In step 204, aggregator 104 receives customer trading data from BOS 102.Control then passes to step 206.

In step 206, aggregator 104 filters, sorts, segregates, and summarizesthe data to produce total and stock counts for determining stockpurchase indices. Aggregator 104 then stores the data in total and stockcounts database 106. Control then passes to step 208.

In step 208, the total and stock counts data is retrieved from database106. Moving average generator 108 processes the total and stock countsdata to determine moving averages for periods of 1, 5, 9, and 21. Periodtime frames are daily or weekly. Stock purchase indices are alsodetermined from the total and stock counts data. Moving index data isthen stored in database 110. Control then passes to step 210.

In step 210, the total and stock counts data, as well as the stockpurchase indices, are used to determine stock ranking. Stock rankingdata is then stored in database 112. Control then passes to step 212.

The process of step 212 is an optional process that is only available tothe user when web site 120 delivery is activated. In step 212, the userhas the option of customizing the output report. Such options include,but are not limited to, filtering the data to allow the user to selectthe results based on business sector, exchange, period, capitalization,country, and different customer investment profile segments; applyingalerts for email delivery When the alert criteria is satisfied; andproviding graphs of other stock indices for comparison with the stockpurchase indices of the present invention.

When the user requests email delivery, the user does not have the optionof customizing the output results of step 212. Step 212 is thereforebypassed for email 118 delivery requests. Control then passes to step214.

In step 214, the results are displayed to the user by user interfacedelivery module 116. Control then passes to step 216 where the processends.

FIG. 3 is a diagram illustrating an architectural overview of thephysical components of stock purchase index system 300, preferablyconnected by a network according to a preferred embodiment of thepresent invention. It should be understood that the particular stockpurchase index system 300 in FIG. 3 is shown for illustrative purposesonly and does not limit the invention. Other implementations forperforming the functions described herein will be apparent to personsskilled in the relevant art(s) based on the teachings contained herein,and the invention is directed to such other implementations.

System 300 comprises a storage device 302 coupled to a processor 304,and a display 306. Storage device 302 houses, inter alia, databases 102,106, 110, 112, 114, and 122. Processor 304 comprises aggregator 104,moving average generator 108, and user interface delivery module 116.Processor 304 processes all of the data generated by aggregator 104,moving average generator 108, and user interface delivery module 116 toprovide the stock purchase indices and generate the display functions.Processor 304 is also coupled to display 306. Display 306 comprises bothemail 118 and web site 120 delivery of results.

More detailed descriptions of the stock purchase index system 300components, as well as their functionality, are provided below.

II. Databases of The Present Invention

Provided below is a description of the contents of a plurality ofdatabases that are utilized by the present invention. It should bereadily apparent to those skilled in the art that the databasesdescribed below are not limited to the described fields, but may includemore fields or less fields, as required.

A. Back Office System (BOS) Database

An exemplary BOS database 102 is shown in FIG. 4. BOS database 102comprises a customer field 402, a holdings field 404, and a transactionsfield 406. Customer field 402 comprises an account number field 408, anownership type field 410, an open date field 407, and a closed date 409.Each customer 402 has a unique account number 408. Ownership type 410comprises government ownership, corporation ownership, investment clubownership, partnerships, sole proprietors, individual regular accounts,and individual retirement accounts.

Government accounts are owned by the government. A government employeemaking decisions on behalf of the government account is subject to therules and regulations of the government. Accounts owned by a corporationallow a financial officer to make the investment decisions. Thefinancial officer is subject to the rules and regulations of thecorporation. Investment clubs are owned by a group of individuals whocollectively make investment decisions. Partnerships are where two ormore persons agree to carry on a business together and share in itsprofits and losses. A single proprietorship is a solely-owned business.

Government accounts, corporate accounts, partnership accounts, andsingle proprietorship accounts are all subject to the rules andregulations of the U.S. Tax Code when it comes to making decisions aboutthe stock market and what, when, and where to invest. An individualretirement account is subject to certain restrictions with respect tomaximum contribution limits and the timing of contributions. Individualregular accounts are owned by individuals who make their own decisionsabout when, what, and where to invest in the stock market. Thus, thetype of ownership account is taken into consideration when determiningstock purchase indices of the present invention.

Open date field 407 indicates the date in which the account was opened.Closed date field 409 indicates the date in which the account wasclosed.

Holdings field 404 comprises a CUSIP field 412 and a number of sharesfield 414. Holdings field 404 contains every instrument currently ownedby customer 402 and the number of shares 414 that are owned for eachinstrument. CUSIP refers to the Committee on Uniform SecurityIdentification Procedure. CUSIP is an inter-industry security codingservice. Each type of security has its own unique CUSIP number. CUSIPfield 412 comprises each security interest held by customer 402. Numberof shares 414 corresponds to the number of shares per CUSIP 412 holding.Although the present invention generally refers to CUSIP 412 as securityinterests, CUSIP 412 may also refer to options, mutual funds, bonds,futures, and currencies.

Transactions field 406 comprises a date field 416, a time field 418, aCUSIP field 419, a number of shares field 420, a value field 422, and abuy or sell field 424. Date field 416 is the date in which customer 402performs transaction 406. Time field 418 is the time in which customer402 performs transaction 406 on date 416. CUSIP 419 lists the securityinterest or instrument that customer 402 transacts on date 416 at time418. Number of shares 420 is the number of shares that customer 402transacts for CUSIP 419 on date 416 at time 418. Value 422 is the tradeprice of CUSIP 419 on date 416 at time 418 multiplied by the number ofshares 420 transacted. Buy or sell field 424 lists whether customer 402in the particular transaction 406 bought or sold CUSIP 419.

BOS database 102 also shows a day trader 426. A day trader is someonewho buys and sells the same CUSIP 419 on the same date 416. In apreferred embodiment of the present invention, day trader data isexcluded from the determination of the stock purchase indices. Daytraders will be further described below.

B. Total and Stock Counts Database

An exemplary total and stock count database 106 is shown in FIG. 5.Database 106 comprises date field 416, CUSIP field 419, buy or sellfield 424, a number of accounts field 502, a number of orders field 504,a number of shares field 506, and a value field 508. Additional records510 and 512 are also kept in database 106 for keeping daily totals offields 502-508.

Number of accounts 502 is the actual number of accounts in the systemthat bought or sold CUSIP 419. Number of orders 504 is the number oforders actually received on date 416 for CUSIP 419. Number of shares 506is the total number of shares transacted on date 416 for CUSIP 419 for abuy or sell 424. Value 508 is the market value of CUSIP 419 on date 416for buy or sell 424 times the number of shares 506 bought or sold. Totalfields 510 and 512 contain the totals for number of accounts 502, numberof orders 504, number of shares 506, and value 508 for each date 416 andfor each buy and sell, respectively.

C. Periods Moving Index Database

An exemplary periods moving index database 110 is shown in FIG. 6. Asstated above, moving average generator 108 extracts the total and stockcounts from database 106 and determines the stock purchase indices andthe moving averages for periods of 1, 5, 9, and 21. The stock purchaseindices, the moving averages, and other weighted data, are stored inperiods moving index database 110. Database 110 comprises a series field602, a period field 604, date field 416, a number of buy accounts field606, a number of sell accounts field 608, a number of buy orders field610, a number of sell orders field 612, a number of shares bought field614, a number of shares sold field 616, a total value bought field 618,a total value sold field 620, a buy weight field 622, a sell weightfield 624, a buy simple index field 626, a sell simple index field 628,a buy weighted index field 630, and a sell weighted index field 632. Itis important to note that each record in database 110 represents thegrand totals of all CUSIPs 419 for the time frame indicated by seriesfield 602, period field 604, and date field 416.

Series field 602 contains data that represents whether each record indatabase 110 contains daily or weekly totals for date 416. Period field604 comprises periods of either 1, 5, 9, or 21. As stated above, movingaverage generator 108 processes the total and stock counts data ofdatabase 110 to determine moving averages for periods of 1, 5, 9, and21. These periods are described for illustrative purposes. The inventionis not limited to these periods.

Number of buy accounts field 606 represents the total number of buyaccounts for series 602 and period 604 on date 416. In a similar manner,number of sell accounts field 608 represents the total number of sellaccounts for series 602 and period 604 on date 416.

Number of buy-orders 610 represents the total number of orders of buyaccounts 606 for series 602 and period 604 on date 416. Number of sellorders 612 represents the total number of orders of sell accounts 608for series 602 and period 604 on date 416.

Number of shares bought 614 represents the total number of shares boughtfor series 602 and period 604 on date 416. Number of shares sold 616represents the total number of shares sold for series 602 and period 604on date 416.

Total value bought 618 is the summary of the total dollar value of thenumber of shares bought 614 for series 602 and period 604 on date 416.Total value sold 620 is the summary of the total dollar value of thenumber of shares sold 616 for series 602 and period 604 on date 416.

It should be noted that number of buy accounts 606, number of sellaccounts 608, number of buy orders 610, number of sell orders 612,number of shares bought 614, number of shares sold 616, total valuebought 618, and total value sold 620 were determined by aggregator 104on a daily basis and stored in total and stock counts database 106. Forexample, referring to FIG. 5, record 510 stores the daily totals fornumber of buy accounts 606, number of buy orders 610, number of sharesbought 614, and total value bought 618. In a similar manner, record 512stores the daily totals for number of sell accounts 608, number of sellorders 612, number of shares sold 616, and total value sold 620.

The present invention provides stock purchase indices (an economicindicator) that measure investor confidence and participation in buyingstocks rather than the value of stocks and which stocks are beingtraded. One stock purchase index is buy simple index 626. Buy simpleindex 626 represents investor confidence and participation in buyingstocks. Another stock purchase index of the present invention is sellsimple index 628. Sell simple index 628 represents investor confidenceand participation in selling stocks. A detailed explanation of how buysimple index 626 and sell simple index 628 are determined is describedbelow with reference to FIGS. 9, 12A, 12B, and 12C.

Weighted stock purchase indices of the present invention are used tominimize the effects that “penny stocks” have on determiningbuyer/seller participation in the stock market. For example, investorsmay purchase a larger number of shares of a “penny stock” than theywould a “blue chip”¹ stock due to the large cost per share of a bluechip stock. ¹ A “blue chip” stock is a stock from a large, safe,prestigious company of the highest class among stock market investments.A “blue chip” company would receive the appellation through beingwell-known, having a large paid-up capital, a good track record ofdividend payments, and skilled management.

There is no set, accepted definition of “penny stocks.” Some peopledefine “penny stocks” as stocks priced under one dollar per share.Others define “penny stocks” as stocks priced under five dollars pershare. Others include only those securities traded in the “pink sheets”²as “penny stocks.” While others include the entire OTC market as “pennystocks.” The Securities Division considers a stock to be a “penny stock”if it trades at or under $5.00 per share and trades in either the “pinksheets” or on NASDAQ. In addition, a true “penny stock” will have lessthan $4 million in net tangible assets and will not have a significantoperating history. In other words, if a company has real assets, such asequipment and inventory, and is engaged in some real business, such asmanufacturing, then the Securities Division does not consider the stockto be “penny stock” even though the shares are low priced. ² “Pinksheets” are a major component of the OTC market. The term “pink sheets”was derived from the fact that these securities are printed on pads oflong, narrow sheets of pink paper.

The present invention accounts for “penny stocks” in determining itsstock purchase indices using buy weight field 622 and sell weight field624 in database 110. Buy weight field 622 represents number of buyaccounts 606 multiplied by the average buy price of the stocks boughtfor series 602 and period 604 on date 416. Sell weight field 624represents number of sell accounts 608 multiplied by the average sellprice of the stocks bought for series 602 and period 604 on date 416.Buy weight 622 and sell weight 624 are used in determining buy weightedindex 630 and sell weighted index 632. Buy weighted index 630 and sellweighted index 632 are both examples of the stock purchase indices ofthe present invention. A detailed explanation of how buy weighted index630 and sell weighted index 632 are determined is described below inreference to FIGS. 11, 12A, 12B, and 12C.

Although database 110 indicates that weighted indices for the stockpurchase indices of the present invention are based on the average buyor sell price, the present invention is not limited to weighting byaverage buy and/or sell price. One skilled in the art would know thatother possible weighting factors such as current market capitalization,future capitalization on growth, market value of customer portfolioholdings, etc., can be used without departing from the scope of thepresent invention.

D. Periods Stock Ranking Database

An exemplary periods stock ranking database 112 is shown in FIGS. 7A and7B. As stated above, moving average generator 108 extracts the total andstock counts data from database 106 and calculates the stock rankingsfor periods of 1, 5, 9, and 21. These calculated rankings, among otherdata, are stored in periods stock ranking database 112. Database 112comprises series field 602, period field 604, date field 416, CUSIPfield 419, number of buy accounts field 606, number of sell accountsfield 608, number of buy orders field 610, number of sell orders field612, number of shares bought field 614, number of shares sold field 616,an average buy price field 702, an average sell price field 704, totalvalue bought field 618, total value sold field 620, buy weight field622, sell weight field 624, a buy simple rank field 706, a sell simplerank field 708, a buy weighted rank field 710, and a sell weighted rankfield 712. It is important to note that each record in database 112represents the totals for each CUSIP 419 for the time frame indicated byseries field 602, period field 604, and date field 416.

Average buy price 702 represents the total value bought 618 divided bythe number of shares bought 614 for CUSIP 419. Average sell price 704represents the total value sold 620 divided by the number of shares sold616 for CUSIP 419. As with buy simple index 626 and sell simple index628, buy simple rank 706, sell simple rank 708, buy weighted rank 710and sell weighted rank 712 are also used as economic indicators ofinvestor confidence and participation in the stock market. Buy simplerank 706 represents the percentage each CUSIP 419 contributes to buysimple index 626. Sell simple rank 708 represents the percentage eachCUSIP 419 contributes to sell simple index 628. In a similar manner, buyweighted rank 710 and sell weighted rank 712 represent the percentageeach CUSIP 419 contributes to buy weighted index 630 and sell weightedindex 632, respectively.

A detailed explanation of how buy simple rank 706 and sell simple rank708 are determined is described below with reference to FIGS. 10, 12A,12B, and 12C. In addition, a detailed explanation of how buy weightedrank 710 and sell weighted rank 712 are determined is described belowwith reference to FIGS. 11, 12A, 12B, and 12C.

E. Other Index Database

As described above, a user may log onto web site 120 to obtain the stockpurchase index report of the present invention. When the user obtainsthe stock purchase index by logging onto web site 120, additionaloptions are available to the user. Such options include, but are notlimited to, viewing the data in conjunction with other indices;filtering the data to allow the user to select the results based onbusiness sector, exchange, period, capitalization, country, anddifferent customer investment profile segments; and setting alerts that,when triggered, provide automatic email delivery of the stock purchaseindex report. Database 114 contains information relating to otherindices, smoothing factors, daily or weekly series, etc. In anotherembodiment of the present invention, database 114 includes customerinvestment profiles. Customer investment profiles can be used to provideadditional information to users beyond stock purchase indices relatingto regular investors only.

An exemplary database 114 representing other types of indices is shownin FIG. 34. Database 114 comprises an other stock indices field 3402 anda plurality of other data fields 3404. Plurality of other data fields3404 relates to the type of indices in stock indices field 3402including, but not limited to, daily or weekly series, dates, andsmoothing factors. Examples of such other stock indices 3402 include aDow Jones Industrial Average 3406, a NASDAQ Composite Index 3408, a NewYork Stock Exchange Composite Index 3410, an American Exchange (Amex)Index 3412, a Russell 2000 Index 3414, etc. The present inventionenables the integration of the stock purchase indices and associatedmeasures with external data sources, such as price indices and investorattitude surveys. A user can construct statistical models using thestock purchase indices as either a dependent or independent explanatoryvariable.

F. Reporting Controls Database

Reporting controls database 122 contains three types of records as shownin FIG. 35. Reporting controls database 122 contains stock descriptiondata 3502, filter controls data 3504, and alert controls data 3506.Exemplary stock description data 3502 is shown in FIG. 36. Exemplaryfilter controls data 3504 is shown in FIGS. 37A and 37B, and exemplaryalert controls data 3506 is shown in FIG. 38.

Exemplary stock description data 3502 is shown in FIG. 36. Stockdescription data 3502 comprises CUSIP field 412, a CUSIP company field3604, an exchange field 3606, a sector field 3608, and a capitalizationfield 3610. Capitalization field 3610 comprises a market value field3612 and a level field 3614. As in BOS database 102, CUSIP 412represents a security interest. CUSIP company 3604 is the name of thecompany issuing CUSIP 412. Exchange 3606 is the type of exchange CUSIP412 is traded on. Examples of the type of exchange include NASDAQ, theNew York Stock Exchange, etc. Sector 3608 is the type of CUSIP 412stock. Examples of sector 3608 includes E Commerce, Communication, etc.

Capitalization 3610 is the level of capital worth of CUSIP company 3604in dollars and its capital level. Market value 3612 is the capital worthof CUSIP company 3604. Level 3614 is the capital level of CUSIP company3604. For example, a “HIGH” indicates a company worth more than $5billion, a “MID” indicates a company worth less than $5 billion and morethan $1 billion, and a “LOW” indicates a company worth $1 billion orless.

Exemplary filter controls data 3504 is shown in FIGS. 37A and 37B.Filter controls data 3504 is used to customize both stock purchase indexreports and stock purchase ranking reports. Filter controls data 3504comprises three main fields: a user field 3702, a filter name field3704, and a filter selections field 3706.

Filter selections field 3706 is comprised of fifteen additional fields.Filter selections field 3706 comprises a stock selection field 3708, aseries type field 3710, a graphical display start date field 3711, anindex measure field 3712, a base smoothing period length field 3714, acomparison smoothing period length field 3716, an ending date field3718, a length of time for change measurement field 3720, a number ofstocks to list field 3722, a first stock listing selection controlsfield 3724, a second stock listing selection controls field 3726, afirst stock ranking selection criteria field 3728, a second stockranking selection criteria field 3730, a comparative index selectionfield 3732, and a series and smoothing selections for comparative indexfield 3734.

Stock selection field 3708 is comprised of three fields includingexchange field 3606, sector field 3608, and a customer segment field3756. In addition, customer segment field 3756 is comprised of threefields including a country investing in field 3758, an age group field3760, and an investment orientation field 3762.

Both first and second stock listing selection controls fields 3724 and3726 are comprised of four fields. First stock listing selectioncontrols field 3724 is comprised of a listing selection field 3736, aperiod length field 3738, a series type field 3740, and an end datefield 3742. Second stock listing selection controls field 3726 is alsocomprised of a listing selection field 3744, a period length field 3746,a series type field 3748, and an end date field 3750.

User 3702 is a registered user of the present system 300. User 3702 mayrequest that a stock purchase index report, including stock ranking, bedelivered to him or her via email 118 or web site 120. Filter name 3704is a name defined by user 3702 for his or her particular filter. Here,once user 3702 defines fields for a filter, the filter can be storedwith associated filter name 3704. This allows user 3702 to reuse thefilter in the future without having to reset the fields. The last mainfield of filter controls data 3504 is filter selections field 3706.Filter selections field 3706 represents the various filters available touser 3702 to customize his or her desired stock purchase index reportand/or ranking report.

Stock selection 3708 represents a variety of options provided to user3702 to filter the types of stocks comprised in the stock purchase indexreport provided. The various options include the exchange 3606 the stockis traded on and stock sector 3608. In addition, stock selection 3708includes customer segment 3756. Customer segment 3756 representsmultiple groups of the trading community, where each group may bedivided into multiple subgroups. For example, one group could subdividecustomers by the country in which they invest in (country investing in3758), such as the United States, Germany, and so forth. Another groupcould subdivide customers by age groups (age group field 3760). Anotherpossible group subdivides customers by investment orientation 3762, suchas for retirement, main income, and so forth. Other possible groups, notshown in FIG. 37, include subdividing customers by nationality,profession, and so forth. An exemplary graphical user interface (GUI)screen for allowing user 3702 to make different stock selections 3708 isshown in FIGS. 28A and 28B and is described in detail below.

Series type 3710 represents whether user 3702 desires the stock purchaseindex report to represent daily or weekly stock totals for ending date3718. An exemplary GUI screen for allowing the user to customize seriestype 3710 is shown in FIG. 18 and is described in detail below. Alsoshown and described below with reference to FIG. 21 is an exemplary GUIscreen for allowing user 3702 to customize ending date 3718.

Graphical display start date field 3711 allows the user to enter abeginning date for the graphical display.

Index measure 3712 is the type of index to be represented by the stockpurchase index report. The types of indices provided by the presentinvention include, but are not limited to, buy simple index 626, sellsimple index 628, buy weighted index 630, and sell weighted index 632.

Base smoothing period length 3714 allows user 3702 to select differentsmoothing period lengths. Base smoothing period lengths 3714 may include5, 9, and 21. Period field 604 comprises periods of either 1, 5, 9, or21. In an alternative embodiment, base smoothing period length 3714includes 5, 10, and 20. This would reduce the processing required bybasing smoothing on any even multiple of 5. Here, the 5 period averageswould be averaged together to create the daily 5 period, as will bedescribed below in detail. An exemplary GUI screen for allowing user3702 to customize smoothing period lengths 3714 is shown in FIG. 19 andis described in detail below.

Comparison smoothing period length 3716 allows user 3702 to selectdifferent smoothing period lengths for comparison with base smoothingperiod length 3714. An exemplary GUI screen for allowing user 3702 tocustomize comparison smoothing period length 3716 is shown in FIG. 20.

Length of time for change measurement 3720 represents the length of timecovered by the change measurements for base smoothing period length 3714and comparison smoothing period length 3716. An exemplary GUI screen forallowing user 3702 to customize length of time for change measurement3720 is shown in FIG. 22 and is described in detail below.

Number of stocks to list 3722 represents the number of stocks providedin the stock purchase ranking lists of the present invention. Anexemplary GUI screen for allowing user 3702 to customize number ofstocks to list 3722 is shown in FIG. 23 and is described in detailbelow.

First stock listing selection controls 3724 allow user 3702 to customizea first stock listing of a stock purchase ranking list. Here, listingselection 3736 (buys or sells), period length 3738 (1, 5, 9, or 21),series type 3740 (daily or weekly), and end date 3742 are customized byuser 3702. An exemplary GUI screen for allowing user 3702 to customizefirst stock listing selection controls 3724 are shown and described withreference to FIG. 24.

Second stock listing selection controls 3726 allow user 3702 tocustomize a second stock listing of a stock purchase ranking report.Here, listing selection 3744 (buys or sells), period length 3746 (1, 5,9, or 21), series type 3748 (daily or weekly), and end date 3750 arecustomized by user 3702. An exemplary GUI screen for allowing user 3702to customize second stock listing selection controls 3726 are shown anddescribed with reference to FIG. 25.

First stock ranking selection criteria 3728 allows user 3702 tocustomize the first stock listing according to various stock purchaseindex parameters. Second stock ranking selection criteria 3730 allowsuser 3702 to customize the second stock listing according to variousstock purchase index parameters. Such stock purchase index parametersmay include, but are not limited to, percent buy simple rank, percentsell simple rank, net percent buy, net percent weighted buy, and soforth. Exemplary GUI screens for first and second stock rankingselection criteria 3728 and 3730 are shown in FIGS. 26 and 27,respectively.

Comparative index selection 3732 allows user 3702 to add a comparisonindices graph for comparing buy simple index 626 to a comparative indexsuch as the NASDAQ or the U.S. High Tech Sector indices. The presentinvention includes not only other stock indices as comparative measures,but also government publications of economic indicators, such as theNational Bureau of Economic Research indices, and survey researchmeasures, such as the Index of Consumer Confidence published by theUniversity of Michigan. Exemplary GUI screens for comparative indexselection 3732 are shown in FIGS. 29A and 29B below.

Series and smoothing selections for comparative index 3734 allows user3702 to alter the displayed comparative index by allowing the selectionof weekly or daily series and moving average smoothing periods for thecomparative index selection. An exemplary GUI screen for series andsmoothing selections for comparative index 3734 is shown in FIG. 30below.

Exemplary alert controls data 3506 is shown in FIG. 38. Alert controlsdata 3506 is used to customize and provide alerts to user 3702 ofparticular changes in the stock purchase indices. Alert controls data3506 comprises five main fields: user field 3702, a user email addressfield 3802, a filters selected field 3804, an alert name field 3806, anda type of alert field 3808. Type of alert field 3808 further comprises achange measurement field 3810 and a gap measurement field 3812. Bothchange and gap measurement fields 3810 and 3812 comprise threeadditional fields. Change measurement field 3810 further comprises anactual percent change field 3814, a percent base field 3816, and aconsistency field 3818. Gap measurement field 3812 further comprises agap size field 3820, a change compared to prior gap field 3822, and aconsistency field 3824.

User email address 3802 is where the present invention sends stockpurchase index and ranking reports to user 3702. Filters selected 3804represents the various filters user 3702 has available to customize hisor her alert email message. Alert name 3806 is a name defined by user3702 for his or her particular alert email message to help bring thealert to user's 3702 attention. Change measurement 3810 is a type ofalert 3808 that is set based on changes from the prior period. Anexemplary GUI screen for actual percent change 3814, percent base change3816, and consistency 3818 are described below with reference to FIG.31. Gap measurement 3812 is a type of alert 3808 that is set based onmeasurements of the gap between the base smoothing period of an index ofthe present invention and the comparison smoothing index of thecomparison index. An exemplary GUI screen for gap size 3820, changecompared to prior gap 3822, and consistency 3824 are described belowwith reference to FIG. 32.

It should be understood that the types of data shown in FIGS. 4, 5, 6,7A, 7B, 36, 37A, 37B, and 38 are for example purposes only and thatother types of data can also be included in databases 102, 106, 110,112, 114, and 122, as would be obvious to one skilled in the relevantart.

III. General System Operation A. Aggregator Creation of Total and StockCounts Database

Aggregator 104 is shown in FIG. 8. Aggregator 104 functions as a shieldto protect individual investor privacy. Aggregator 104 also functions asa sieve to sift out unwanted records, separate records into categories,and count daily totals. Aggregator 104 comprises a filter 802, aplurality of sorters 804, 808, and 810, a segregator 806, a plurality ofcounters 812-818 and 828-834, and a plurality of summation indicators820-826 and 836-842.

Filter 802 is coupled to sorter 804. Sorter 804 is coupled to segregator806. Segregator 806 is coupled to sorters 808 and 810. Sorter 808 iscoupled to counters 812-818 and summation indicators 820-826. Sorter 810is coupled to counters 828-834 and summation indicators 836-842.Counters 812-818 and 828-834 are coupled to totals & stock countsdatabase 106. Summation indicators 820-826 and 836-842 are also coupledto totals & stock counts database 106.

Filter 802 is used to eliminate suspected seasonal data. In a preferredembodiment, filter 802 eliminates all accounts except individual regularaccounts. In another embodiment, filter 802 eliminates all accountsexcept individual regular accounts and sole proprietorship accounts. Inyet another embodiment, filter 802 eliminates all accounts exceptindividual regular accounts, sole proprietorship accounts, andpartnership accounts.

Alternatively, filter 802 could be used to treat and remove the seasonalcomponent from retirement accounts as well as other accounts that maycontain seasonal data using the U.S. Census Bureau's X11 procedure.

Sorter 804 is used to sort out multiple records that show a buy orderand a sell order for the same account number 408 and CUSIP 419 on thesame date 416. Such a scenario having a buy order and a sell order fromthe same account number 408 for the same CUSIP 419 on the same date 416indicates a “day trader.” One embodiment of the present invention isdirected to “investors” and not “day traders.” It should be noted thatanother embodiment of the present invention may not only include “daytraders,” but also growth oriented or income oriented investors.Referring back to FIG. 4, BOS database 102 includes a day trader 426.Customer 402 having account number 408 of “9921” is day trader 426. Asshown in database 102, the same number of shares 420 (“1000”) was bothbought and sold for the same CUSIP 419 (“AMT”) on the same date 416(“Jan. 5, 1999”) by account number 408 (“9921”). As stated previously,in a preferred embodiment of the present invention, all day traders 426are eliminated from the stock purchase indices of the present invention.

Referring back to FIG. 8, once all day traders 426 have been eliminated,segregator 806 divides the remaining records into buys and sells. Asnapshot of how the data in BOS database 102 is organized aftersegregation by segregator 806 is shown below in Table 1. As can be seenin Table 1, day trader 426 has been eliminated.

TABLE 1 Buy or Account No. of No. of Date Sell CUSIP No. Orders SharesValue Jan. 4, 1999 Buy AMT 1234 1 50 $500 Jan. 4, 1999 Buy AMT 3455 1 50$500 Jan. 4, 1999 Buy AMT 7210 2 250 $2,500 Jan. 5, 1999 Buy AMT 4266 1355 $3,195 . . . . . . . . . . . . . . . . . . Jan. 4, 1999 Sell AMT6978 3 500 $6,000 Jan. 4, 1999 Sell AMT 4467 1 200 $1,000 Jan. 5, 1999Sell AMT 3499 1 350 $3,500 . . . . . . . . . . . . . . . . . . . . .Jan. 4, 1999 Buy MSF 1234 1 500 $4,000 Jan. 4, 1999 Buy MSF 2855 1 1000$8,000 Jan. 5, 1999 Buy MSF 4900 1 1000 $11,000 Jan. 5, 1999 Buy MSF4523 1 1000 $11,000 . . . . . . . . . . . . . . . . . . Jan. 4, 1999Sell MSF 3980 1 800 $5,600 Jan. 4, 1999 Sell MSF 2583 2 3000 $21,000Jan. 5, 1999 Sell MSF 4266 1 100 $150 . . . . . . . . . . . . . . . . .. Jan. 4, 1999 Buy CMQ 2583 1 1000 $5,000 . . . . . . . . . . . . . . .. . . Jan. 4, 1999 Sell GET 1988 1 200 $4,000 . . . . . . . . . . . . .. . . . .

Sorters 808 and 810 sort the buy and sell records respectively, by CUSIP419. Aggregator 104 then counts and sums various transactional valuesfor each date 416 according to CUSIP 419. Aggregator 104 also counts andsums transactional values for each date 416, for all CUSIPs 419, toproduce daily totals. A detailed description of how aggregator 104counts and sums values for each date 416 by CUSIP 419 will be explainedfirst. A detailed description of how aggregator 104 counts and sumsvalues for each date 416, for all CUSIPs 419, will follow.

Referring now to both FIGS. 5 and 8, counters 812 and 828 count thenumber of buy and sell orders 504 for each CUSIP 419. Counters 816 and832 count the number of accounts 502 that bought or sold a particularCUSIP 419 on date 416, respectively. The market value of CUSIP 419refers to the value of its stock (at the time it was traded) multipliedby the number of shares 506 traded. Summation indicators 820 and 836 sumthe market values 508 for each CUSIP 419 bought or sold on date 416,respectively. Summation indicators 824 and 840 sum the number of shares506 bought or sold, respectively, for a particular CUSIP 419.

A detailed description of how aggregator 104 counts and sums values foreach date 416, independent of CUSIP 419, will now be explained. Counters814 and 830 count the total number of orders 504 for all CUSIPs 419bought and sold on date 416, respectively. Counters 818 and 834 countthe total number of accounts 502 that bought or sold stock,respectively, on date 416. Summation indicators 822 and 838 sum thetotal market value for all CUSIPs 419 bought and sold, respectively ondate 416. Summation indicators 826 and 842 sum the total number ofshares bought and sold, respectively, on date 416. Note that the totalmarket value and the total number of shares cannot be determined bysummation indicators 822, 826, 838, and 842 until all CUSIP totals fordate 416 have been determined. These totals are then stored in records510 and 512 of total and stock counts database 106 for later use bymoving average generator 108.

B. Moving Average Generator Creation of Buy Simple Index and Sell SimpleIndex

As stated above, moving average generator 108 calculates the stockpurchase indices of the present invention. Such indices include buysimple index 626 and sell simple index 628. FIG. 9 represents a flowdiagram 900 of the method used to determine buy simple index 626. Theprocess begins with step 902 where control is immediately passed to step904. In step 904, the total and stock counts from records 510 and 512 ofdatabase 106 are read into memory. Control then passes to step 906.

In step 906, the total number of investors are determined for eachseries 602, period 604, and date 416. The number of investors isdetermined by number of buy accounts 606 plus number of sell accounts608. Control then passes to step 908.

In step 908, buy simple index 626 is determined. Buy simple index 626 isdetermined by number of buy accounts 606 divided by the number ofinvestors. Control then passes to step 910 where the process ends.

In a similar manner, sell simple index 628 is determined. Sell simpleindex 628 is determined by number of sell accounts 608 divided by thenumber of investors.

C. Moving Average Generator Creation of Buy Simple Rank, Sell SimpleRank, Buy Weighted Index, and Sell Weighted Index

As previously stated, moving average generator 108 determines the stockpurchase indices of the present invention, including buy weighted index630 and sell weighted index 632. FIGS. 10A and 10B represent a flowdiagram 1000 of the method used to determine buy weighted index 630,sell weighted index 632, buy simple rank 706, and sell simple rank 708.In FIG. 10A, the process begins with step 1002 where control isimmediately passed to step 1004.

In step 1004, counters are initialized. Specifically, a total buy weightcounter and a total sell weight counter are initialized to zero. Controlthen passes to step 1006.

In step 1006, an iterative loop process begins for determining buyweighted index 630, sell weighted index 632, buy simple rank 706, andsell simple rank 708 for each CUSIP 419. This iterative loop process isrepeated for each CUSIP 419 sold on day 416. Control then passes to step1008.

In step 1008, all required data from total and stock counts database 106for the current CUSIP are read into memory. Control then passes to step1010.

In step 1010, buy simple rank 706 is determined. Buy simple rank 706 isequal to number of buy accounts 606 divided by the number of investors.As described above with reference to FIG. 9, the number of investors isdetermined by number of buy accounts 606 plus number of sell accounts608. Control then passes to step 1012.

In step 1012, sell simple rank 708 is determined. Sell simple rank 708is equal to number of sell accounts 608 divided by the number ofinvestors. Control then passes to step 1014.

In step 1014, average buy price 702 is determined. Average buy price 702is equal to total value bought 618 divided by number of shares bought614. Control then passes to step 1016 in FIG. 10B.

In step 1016, average sell price 704 is determined. Average sell price704 is equal to total value sold 620 divided by number of shares sold616. Control then passes to step 1018.

In steps 1018 and 1020, buy weight 622 and sell weight 624 aredetermined, respectively. In step 1018, buy weight 622 is equal toaverage buy price 702 multiplied by number of buy accounts 606. Controlthen passes to step 1020.

In step 1020, sell weight 624 is equal to average sell price 704multiplied by number of sell accounts 608. Control then passes to step1022.

In steps 1022 and 1024, the total buy weight and the total sell weightare determined, respectively. In step 1022, the total buy weight isequal to the previously determined total buy weight plus current buyweight 622. Control then passes to step 1024.

In step 1024, the total sell weight is equal to the previouslydetermined total sell weight plus current sell weight 624. Control thenpasses to step 1026.

In step 1026, for the current CUSIP 419, buy simple rank 706, sellsimple rank 708, average buy price 702, average sell price 704, buyweight 622, and sell weight 624 are stored in memory. Control thenpasses to decision step 1028.

In decision step 1028, it is determined whether the current CUSIP 419 isthe last CUSIP 419 for the same period for day 416. If the current CUSIP419 is not the last CUSIP 419, control passes back to step 1008 in FIG.10A where the process is repeated for the next CUSIP 419.

Referring back to step 1028, if it is determined that the current CUSIP419 is the last CUSIP 419 for the same period on day 416, then controlpasses to step 1030.

In step 1030, the total weight is determined. The total weight is equalto the total buy weight plus the total sell weight. Control then passesto step 1032.

In step 1032, buy weighted index 630 is determined. Buy weighted index630 is equal to the total buy weight divided by the total weight.Control then passes to step 1034.

In step 1034, sell weighted index 632 is determined. Sell weighted index632 is equal to the total sell weight divided by the total weight.Control then passes to step 1036.

In step 1036, buy weighted index 630, sell weighted index 632, buysimple rank 706, and sell simple rank 708 are stored in database 110 forfuture display to a user. Control then passes to step 1038 where theprocess ends.

D. Moving Average Generator Creation of Buy Weighted Rank and SellWeighted Rank

Moving average generator 108 also calculates buy weighted rank 710 andsell weighted rank 712. FIG. 11 represents a flow diagram 1100 of themethod used to determine buy weighted rank 710 and sell weighted rank712 of the present invention. The process begins with step 1102 wherecontrol is immediately passed to step 1104.

In step 1104, buy weight 622, sell weight 624, and the total weight (allcalculated in flow diagram 1000) are read from memory. Control thenpasses to step 1106.

In step 1106, buy weighted rank 710 is determined. Buy weighted rank 710is equal to buy weight 622 divided by the total weight. Control thenpasses to step 1108.

In step 1108, sell weighted rank 712 is determined. Sell weighted rank712 is equal to sell weight 624 divided by the total weight. Controlthen passes to step 1110.

In step 1110, buy weighted rank 710 and sell weighted rank 712 arestored in database 112 for future selection ranking and display to auser. Control then passes to step 1112 where the process ends.

FIGS. 12A, 12B, and 12C contain examples of specific values for buy andsell simple ranks 706 and 708, buy and sell weighted ranks 710 and 712,buy and sell simple indices 626 and 628, and buy and sell weightedindices 630 and 632.

E. Smoothing Techniques

To reduce the amount of data variation that is generated from dailytallies of the stock purchase indices, smoothing techniques over aperiod of time are employed. The smoothing technique used by the presentinvention is a moving average that is determined for periods of 5, 9,and 21 days or weeks. A weighted moving average formula 1302 used tosmooth the stock purchase indices data is shown in FIG. 13. Data inweighted moving average formula 1302 is weighted by the number ofinvestors. Stock purchase indices data is stored as an array of recordssorted by date, with the last array element being the most current day'srecord. The (k−i+1) index is used to represent the current day's recordsas well as the record's offset from the current day to the periodcovered. For example, a five-day period beginning on ending date Jan. 8,1999 uses records of Jan. 8, 1999-Jan. 4, 1999.

The method used to generate a 5, 9, or 21 period average is shown inFIG. 14. The process begins with step 1402 where control is passed tostep 1404.

In step 1404, k is set equal to 5, where k is the period. Control thenpasses to step 1406.

In step 1406 variables are initialized. Here, sum is set equal to 0,total is set equal to 0, and i is set equal to 1. The variable sum isused to sum the stock purchase index times the number of investors foreach day within the period. The variable total is used to sum the numberof investors for each day within the period. Control then passes to step1408.

In step 1408, sum is set equal to the previously determined sum plusindex_((k−i+1)) times the number of investors_((k−i+1)). Control thenpasses to step 1410.

In step 1410, total is set equal to the previously determined total plusthe number of investors_((k−i+1)). Control then passes to step 1412.

In step 1412, i is incremented by 1 in order to select the previous dayor week in period k. Control then passes to decision step 1414.

In decision step 1414, if it is determined that i is less than or equalto k, control passes back to step 1408 where the sum and the totals aredetermined for each day or week within period k, and where i isincremented.

Referring back to decision step 1414, if it is determined that i isgreater than k, all the data for the current period k has beendetermined. Control then passes to step 1416.

In step 1416, the moving average index for period k is determined. Themoving average index is equal to the sum divided by the total. Controlthen passes back to step 1404 where the process repeats for movingaverages of k=9 and/or k=21 are determined. Once the moving averages forall three periods have been calculated, control then passes from step1416 to 1418 where the process ends.

An example 1500 of a five (5) period moving average is shown in FIG. 15.Five (5) period moving averages are determined by applying formula 1302to the current and four preceding daily or weekly stock purchase indexresults. Example 1500 is a five (5) period daily moving average. A first5-day period average is shown in a record 1514. In record 1514, buysimple index 1512 of 49% was determined by using daily totals fromending date Jan. 8, 1999 through starting date Jan. 4, 1999 (i.e.,((60%*6)+(45%*5)+(48%*11)+(53%*7)+(42%*8))/(6+5+11+7+8)=49%). A second5-day period average is shown in a record 1516. In record 1516, buysimple index 1512 of 49% was determined by using daily totals fromending date Jan. 11, 1999 through starting date Jan. 5, 1999 (i.e.,((45%*5)+(48%*11)+(53%*7)+(42%*8)+(56%*9))/(5+11+7+8+9)=49%). As can beseen from the dates used in the determination of record 1516, a newmoving average is determined by dropping the oldest of the 5 precedingstock purchase index results and adding the sixth now current day stockpurchase index results and reapplying formula 1302 to determine theaverage as shown in record 1516. Note that market holidays and weekendswill be adjusted to include only trading days in the period average.This continues as each new daily stock purchase index results areavailable at market close. The 5-day moving averages that result onFriday, or the end of the trading week, are used to generate the weeklyperiod series. This weekly series is then used as the basis for asimilar process to determine weekly moving averages.

For periods of 9 and 21 the above process is repeated with the exceptionthat in the case of the 9 period, formula 1302 uses the current day orweek and the 8 preceding daily or weekly stock purchase index results,and for the 21 period formula, the 21^(st) day or week and the 20preceding daily or weekly stock purchase index results are used.

F. Time Series Analysis

Time series decomposition involves analysis of the recurring andperiodic variations in data, especially economic series. All time seriesinclude trend, cycle, seasonal, and irregular components expressed asthe following formula:Time Series=trend*cycle*seasonal*irregularThe purpose of our statistical treatment is to remove the irregular andseasonal factors from the data so as to have a clear measure of anytrend and cycle variations in buyer purchasing. The irregular componentor “noise” is removed by applying a moving average. The seasonalcomponent is removed by aggregator 104 by removing undesirable records.For example, aggregrator 104 removes all individual retirement accountsas described above and puts them into a separate time series. A seasonalcomponent is a recurring variation up or down that occurs in a timeseries at about the same time each year. A seasonal component could berelated to year-end tax requirements such as a deadline for whenindividual retirement accounts contributions have to be deposited. Thisseasonal component could be measured using a ratio to moving averagetechnique if there is a sufficient number of periods to apply theanalysis.

By segregating out the individual retirement accounts and theirseasonable component and by using a moving average to remove theirregular component, we have isolated the trend and cycle components.Now,TimeSeries=(trend*cycle*seasonal*irregular)/(seasonal*irregular)=trend*cycle.This focuses on the desired measurement of variation in how investorparticipation relates to economic trend and business cycles.

The impact of applying the moving average, and thus removing theirregular component or “noise” from the time series data, is seen bycomparing the graphs in FIGS. 16A, 16B, and 17. FIGS. 16A, 16B, and 17represent standard default reports of buy simple index 626. FIG. 16Arepresents a daily buy simple index in which no smoothing techniqueswere applied. The data in FIG. 16A is very irregular or “noisy.” FIG.16B uses a 5 period smoothing technique in which the data is averagedover a 5-day (or weekly) period. FIG. 16B exhibits data that is less“noisy” than FIG. 16A. FIG. 17 provides a 9 and 21 period weeklysmoothing technique. FIG. 17 exhibits data that is the least “noisy.”

As illustrated by FIGS. 16A, 16B, and 17, the longer the time periodused for smoothing the less variation or “noise” there is in the data.Although a long time period for smoothing would produce the most stableand smoothest line, there is a disadvantage to using a long time period.The disadvantage is a loss of sensitivity to changes and the delay inproviding the signal of the changes. What is needed is a balance betweenthe desired sensitivity and the desired stability. This balance leads tothe use of combinations of smoothing periods, one more sensitive with ashort period for smoothing such as 9, and one for more stability such asa 21 period average. By using these combinations of different periods,we can most clearly see the pattern in changes. When the 9 periodaverage crosses the 21 smoothing line and stays consistently above itfor some period of time, then the underlying series is rising. When the9 period average goes below and stays consistently below the 21 periodaverage, then the underlying series is falling.

IV. Graphical User Interface

The user interface delivery module 116 allows a subscriber to receive astandard default report. The standard default report can be delivered tothe subscriber via electronic mail (email) 118 by service subscription.Alternatively, the subscriber can actually use the system to selectvarious output configurations by logging onto the service's web site120. Web site 120 provides a graphical user interface that allows theuser to personalize the analysis by applying filters and alerts.

The filters allow a user to select subsets of the data as well as viewthe data over different periods of time. The filters also allow a userto expand the stock ranking list to view more than the default top tenstocks bought and sold. Other indices may also be selected forcomparison with the stock purchase indices.

Web site 120 users can also have email 118 delivery. Web site 120 userscan establish criteria as to when a report can be sent by email 118based on a change in the index from period to period or when the gapdifference between two selected period measurements exceeds a specifiedlimit. This is accomplished using alerts.

An exemplary standard daily default email report 1600 of the buy simpleindex 626 is shown in FIG. 16A. Standard daily default email report 1600comprises a graphical representation of a 1 period daily buy simpleindex 1602, an ending date that the report issues 1604, and a numericalvalue for the most current buy simple index 1606. Graph 1602 shows howthe buy simple index 626 varies over time. Default email report 1600further comprises the change from the previous day's buy simple index1608 and lists of the current day's top ten stocks bought 1610 and topten stocks sold 1612. The current day's top ten stocks bought 1610 andtop ten stocks sold 1612 include the buy and sell percentage for eachstock listed, respectively.

An exemplary standard weekly default email report 1620 of buy simpleindex 626 is shown in FIG. 16B. Standard weekly default email report1620 comprises a graphical representation of a 1 period weekly buysimple index 1622, a date that the report issues 1624, and a numericalvalue for the most current buy simple index 1626. Graph 1622 shows howthe buy simple index 626 varies over time. Default email report 1620further comprises the change from the previous week's buy simple index1628 and lists of the current week's top ten stocks bought 1630 and topten stocks sold 1632. The current week's top ten stocks bought 1630 andtop ten stocks sold 1632 include the buy and sell percentage for eachstock listed, respectively.

FIG. 17 is an exemplary standard default web site report 1700 of buysimple index 626 as seen by users that log onto the service's web site120. Standard default web site report 1700 comprises a base seriesgraphical representation of a 9 period weekly buy simple index 1701, acomparison series graphical representation of a 21 period weekly buysimple index 1702, a first numerical value of the weekly buy simpleindex for the most current 9-week period 1705, a second numerical valueof the weekly buy simple index for the most current 21-week period 1704,a first measurement change from the previous week for the 9-week period1707, a second measurement change from the previous week for the 21-weekperiod 1706, and a gap measurement 1708, representing the differencebetween the ending reported 9 period average versus the 21 periodaverage. Although the base series graph and the comparison series graphare presented for the 9 and 21 period weekly buy simple index, it shouldbe readily apparent to those skilled in the art that other period timeframes can be used for the base and comparison series graphs. Standarddefault web site report 1700 further includes lists of the currentweek's top ten stocks bought 1630 and top ten stocks sold 1632. Thecurrent week's top ten stocks bought 1630 and top ten stocks sold 1632include the buyer and seller percentage for each stock listed,respectively.

As previously stated, a user logging onto web site 120 has the abilityto customize the output. Customization of the output is provided via theuse of filters and alerts. Filters and alerts are enabled when a userselects a desired parameter to be changed on the graphical display. Theuser can select the desired parameter to be changed by positioning thecursor on the parameter and right clicking on that parameter using amouse. The location or spot in which the user right clicks is referredto as a hot spot. Right clicking on the hot spot activates a user helpfunction and causes a filter or an alert display arrow to appear. Thedisplay arrow includes instructions and explanations of filter and alertfunctions. The user can also left click on the hot spot to activate acontrol selection window. Left clicking on the hot spot causes thecontrol selection window to appear. The control selection windowcomprises a list of possible choices to change the desired parameter.The user can position the cursor on one of the choices presented in thecontrol selection window and double click on the mouse to activate thenew selection. Double clicking the mouse updates the displayed resultsaccording to the new parameter selection. After the display is updated,the display arrow and control selection box are no longer shown on thedisplay. A detailed description of the types of filters that can beapplied by a user to customize the output is described below. Thefollowing description will be better understood if read in conjunctionwith filter controls database 3504, shown in FIGS. 37A and 37B.

FIG. 18 illustrates the application of a filter to select a daily orweekly series for standard default web site report 1800. The desiredparameter to be changed is series type 3710. Series type 3710 parameteris presently set to “Weekly” in FIG. 18. Positioning the cursor withinor in close proximity to the parameter “Weekly” and right clicking usingthe mouse causes a display arrow 1802 to appear. The area surroundingthe parameter “Weekly” is now referred to as a hot spot 1804. Hot spot1804 is shown in phantom. Display arrow 1802 points directly to seriestype 3710 parameter. Positioning the cursor within hot spot 1804 andusing a left click will cause a control selection window 1806 to appear.Control selection window 1806 comprises series type 3710 parameters andstart date 3711. The user can change series type 3710 parameter from“Weekly” to “Daily” by double clicking the mouse on the desiredselection. The user can also enter a start date 3711 for the graphicaldisplay.

FIG. 19 illustrates the application of a filter to select differentsmoothing period lengths. The desired parameter to be changed is basesmoothing period length 3714. Base smoothing period length 3714 ispresently set to “9 Period” in FIG. 19. Positioning the cursor within orin close proximity to the parameter “9 Period” and right clicking usingthe mouse causes a display arrow 1802 to appear. The area surroundingthe parameter “9 Period” is now hot spot 1804. Hot spot 1804 is shown inphantom. The user can also position the cursor within hot spot 1804 andleft click the mouse to cause control selection window 1806 to appear.Control selection window 1806 provides a list of all of the desired basesmoothing period lengths that can be selected by the user. Basesmoothing period length 3714 parameters include 1 (indicating nosmoothing), 5, 9, and 21. The user can now select the desired basesmoothing period length 3714 parameter by double clicking the mouse onthe desired selection.

FIG. 20 illustrates the application of a filter to select differentsmoothing period lengths for comparison series 1702. The desiredparameter to be changed is comparison smoothing period length 3716.Comparison smoothing period length 3716 is presently set to “21 Period”in FIG. 20. Positioning the cursor within or in close proximity to theparameter “21 Period” and right clicking using the mouse causes displayarrow 1802 to appear. The area surrounding the parameter “21 Period” isnow hot spot 1804. Hot spot 1804 is shown in phantom. The user can alsoposition the cursor within hot spot 1804 and left click the mouse tocause control selection window 1806 to appear. Control selection window1806 provides a list of all of the desired comparison smoothing periodlengths that can be selected by the user. Comparison smoothing periodlength 3716 parameters include 1 (indicating no smoothing), 5, 9, and21. The user can now select the desired comparison smoothing periodlength 3716 parameter by double clicking the mouse on the desiredselection.

FIG. 21 illustrates the application of a filter to select an ending datefor period-to-period change reporting and stock listings. The desiredparameter to be changed is ending date 3718. Ending date 3718 parameteris presently set to “Jan. 8, 1999” in FIG. 21. Note that the defaultfilter setting for the ending date is always the current date, but theuser can select other dates for comparison. The ending date 3718selected will be used as the default for filter stock listing selectioncontrols 3724 and 3726, as shown in FIGS. 24 and 25. The current endingdate is automatically reset when the user has completed his or heranalysis. Positioning the cursor within or in close proximity to theparameter “Jan. 8, 1999” and right clicking using the mouse causesdisplay arrow 1802 to appear. The area surrounding the parameter “Jan.8, 1999” is now hot spot 1804. Hot spot 1804 is shown in phantom. Theuser can also position the cursor within hot spot 1804 and left clickthe mouse to cause control selection window 1806 to appear. Controlselection window 1806 provides a list of all of the desired ending dates3718 that can be selected by the user. The user can now select thedesired ending date 3718 parameter by double clicking the mouse on thedesired selection. The change of ending date 3718 also causes a changein top ten stocks bought 1630, top ten stocks sold 1632, first numericalvalue of the weekly buy simple index for the most current 9-week period1705, second numerical value of the weekly buy simple index for the mostcurrent 21-week period 1704, first measurement change from the previousweek for the 9-week period 1707, second measurement change from theprevious week for the 21-week period 1706, and gap measurement 1708.

FIG. 22 illustrates the application of a filter that allows the lengthof time covered by first measurement change 1707 and second measurementchange 1706 to be changed. The desired parameter to be changed is lengthof time for change measurement 3720. Length of time for changemeasurement 3720 is presently set to “1” in FIG. 22. Positioning thecursor within or in close proximity to the parameter “1” and rightclicking using the mouse causes display arrow 1802 to appear. The areasurrounding the parameter “1” is now hot spot 1804. Hot spot 1804 isshown in phantom. The user can also position the cursor within hot spot1804 and left click the mouse to cause control selection window 1806 toappear. Control selection window 1806 provides an entry line for whichthe user can type in the desired length of time for change measurement3720 and press “Enter.” Note that beside the entry line is the currentsetting of length of time for change measurement 3720.

FIG. 23 illustrates the application of a filter for changing the numberof stocks listed in the top ten stocks bought 1630 and top ten stockssold 1632. The desired parameter to be changed is number of stocks tolist 3722. Number of stocks to list 3722 is presently set to “10” inFIG. 23. Positioning the cursor within or in close proximity to theparameter “10” and right clicking using the mouse causes display arrow1802 to appear. The area surrounding the parameter “10” is now hot spot1804. Hot spot 1804 is shown in phantom. The user can also position thecursor within hot spot 1804 and left click the mouse to cause controlselection window 1806 to appear. Control selection window 1806 providesan entry line for which the user can enter the desired number of stocksto list 3722 and press “Enter.” Note that to the right of the entry lineis the current setting of number of stocks to list 3722.

FIG. 24 illustrates the application of a filter that allows the firststock listing selections to be changed. The desired parameters to bechanged are listing selection 3736, period length 3738, series type3740, and end date 3742 for first stock listing selection controls 3724.Positioning the cursor within or in close proximity to the parameter“Weekly Buys” and right clicking using the mouse causes display arrow1802 to appear. The area surrounding the parameter “Weekly Buys” is nowhot spot 1804. Hot spot 1804 is shown in phantom. The user can alsoposition the cursor within hot spot 1804 and left click the mouse tocause control selection window 1806 to appear. Control selection window1806 provides four fields: listing selection 3736, period length 3738,series type 3740, and end date 3742 for which the user can double clickon each of them to change parameter settings. Double clicking on listingselection 3736 parameter (that is, “Buys”) causes listing selection 3736parameter to toggle back and forth between “Buys” and “Sells.” Doubleclicking on period length 3738 parameter allows the user to enter thedesired period. Double clicking on series type 3740 (that is, “Weeks”)causes series type 3740 to toggle between “Weeks” and “Days.” Doubleclicking on end date 3742 allows the user to enter the desired end date.The user indicates that all parameters have been entered correctly bydouble clicking on “Enter Overrides.”

FIG. 25 illustrates the application of a filter for allowing the secondstock listing selections to be changed. The desired parameters to bechanged are listing selection 3744, period length 3746, series type3748, and end date 3750 for second stock listing selection controls3726. Positioning the cursor within or in close proximity to theparameter “Weekly Sells” for the second stock listing and right clickingusing the mouse causes display arrow 1802 to appear. The areasurrounding the parameter “Weekly Sells” is now hot spot 1804. Hot spot1804 is shown in phantom. The user can also position the cursor withinhot spot 1804 and left click the mouse to cause control selection window1806 to appear. Control selection window 1806 provides four fields:listing selection 3744, period length 3746, series type 3748, and enddate 3750 for which the user can double click on each of them to changeparameter settings. Double clicking on listing selection 3744 parameter(that is, “Sells”) causes listing selection 3744 parameter to toggleback and forth between “Buys” and “Sells.” Double clicking on periodlength 3746 parameter allows the user to enter the desired period.Double clicking on series type 3748 (that is, “Weeks”) causes seriestype 3748 to toggle between “Weeks” and “Days.” Double clicking on enddate 3750 allows the user to enter the desired end date. The userindicates that all parameters have been entered correctly by doubleclicking on “Enter Overrides.”

FIG. 26 illustrates the application of a filter for allowing the firststock ranking selection criteria to be changed. The desired parameter tobe changed is first stock ranking selection criteria 3728. Positioningthe cursor within or in close proximity to the parameter “% Buyers” andright clicking using the mouse causes display arrow 1802 to appear. Thearea surrounding the parameter “% Buyers” is now hot spot 1804. Hot spot1804 is shown in phantom. The user can also position the cursor withinhot spot 1804 and left click the mouse to cause control selection window1806 to appear. Control selection window 1806 provides a list of all ofthe desired first stock ranking selection criteria 3728 that can beselected by the user. First stock ranking selection criteria 3728include % Buy Simple Rank, % Sell Simple Rank, % Buy Weighted Rank, %Sell Weighted Rank, Net % Buy, Net % Weighted Buy, % Shares Bought, %Shares Sold, % Shares Traded, % Value Bought, % Value Sold, and % Value.The user can now select the desired first stock ranking selectioncriteria 3728 by double clicking the mouse on the desired selection. Thecircle displayed around “% Buy Simple Rank” indicates that “% Buy SimpleRank” is the selection.

FIG. 27 illustrates the application of a filter that enables the secondstock ranking selection criteria to be changed. The desired parameter tobe changed is second stock ranking selection criteria 3730. Positioningthe cursor within or in close proximity to the parameter “% Buy W” andright clicking using the mouse causes display arrow 1802 to appear. Thearea surrounding the parameter “% Buy W” is now hot spot 1804. Hot spot1804 is shown in phantom. The user can also position the cursor withinhot spot 1804 and left click the mouse to cause control selection window1806 to appear. Control selection window 1806 provides a list of all ofthe desired second stock ranking selection criteria that can be selectedby the user. Second stock ranking selection criteria 3730 includes % BuySimple Rank, % Sell Simple Rank, % Buy Weighted Rank, % Sell WeightedRank, Net % Buy, Net % Weighted Buy, % Shares Bought, % Shares Sold, %Shares Traded, % Value Bought, % Value Sold, and % Value. The user cannow select the desired second stock ranking selection criteria 3730 bydouble clicking the mouse on the desired selection. The circle displayedaround “% Buy W” indicates that “% Buy W” is the selection.

FIGS. 28A and 28B illustrate the application of a filter for enablingall of the underlying stocks included in the stock purchase index to bechanged. The desired parameter to be changed is stock selection 3708.Positioning the cursor within or in close proximity to the title of thegraph and right clicking using the mouse causes display arrow 1802 toappear. The area surrounding the title of the graph is now hot spot1804. Hot spot 1804 is shown in phantom. The user can also position thecursor within hot spot 1804 and left click the mouse to cause controlselection window 1806 to appear. Control selection window 1806 providesa list of all of the desired stock selections 3708 that can be selectedby the user. Stock selection 3708 includes: exchange 3606,capitalization 3610, sector 3608, and customer segment 3756. Stocks canbe changed by changing the exchange the stock is listed on, the level ofmarket capitalization, business sector, and customer segments. Exchange3606 refers to the stock exchange that the actual stocks are listed on.Capitalization refers to the market value of the stock, that is, whetherit is a penny stock, a mid-range stock, or a large capitalization stock.Sector 3608 refers to the different types of businesses, such asutilities, high tech stocks, industrials, transportation, airlines, etc.Customer segment 3756 refers to whether the customers are Americans orforeign nationals, whether the customers are high risk investors or lowrisk investors, etc. As shown in selection window 1806, sector waschosen to be U.S. high tech stocks. This selection is reflected in FIG.28B where the title 2816 is revised to indicate “U.S. High Tech SectorPurchase Index.” All of the graphs and data of FIG. 28B reflect the newstock selection 3708 of “High Tech Stocks.”

FIGS. 29A and 29B illustrate the addition of a comparison indices graphfor comparing buy simple index 626 to a comparative index. The desiredparameter to be changed is comparative index selection 3732. Positioningthe cursor on the graph itself and right clicking using the mouse causesdisplay arrow 1802 to appear. The user can left click the mouse to causecontrol selection window 1806 to appear. Control selection window 1806provides a list of some of the desired comparative index selection3732's that can be selected by the user by double clicking on thedesired comparative index. Such comparative indices include, but are notlimited to, Biotech, Dow Jones Composite, Dow Jones Industrials, U.S.High Tech, NASDAQ stock index, etc. Selecting one of the comparativeindex selection 3732's, causes the top 10 stock buys and top 10 stockssold to be replaced with comparative index graphs 2902 and 2904(representative of 9 period and 21 period comparative index graphs,respectively) shown in FIG. 29B. These additional graphs allow thedirect comparison of the buy simple index in order to better understandthe relationship between the indices.

FIG. 30 illustrates the application of a filter that enables a displayedcomparative index to be altered by allowing the selection of weekly ordaily series and moving average smoothing periods for the comparativeindex selection. The desired parameters to be changed are series typeand smoothing selections for comparative index 3734. Positioning thecursor on the comparative index graph and right clicking using the mousecauses display arrow 1802 to appear. The area surrounding thecomparative index graph is now hot spot 1804. Hot spot 1804 is shown inphantom. The user can also position the cursor within hot spot 1804 andleft click the mouse to cause control selection window 1806 to appear.Control selection window 1806 provides a list of all of the currentsettings for the series type and smoothing selections for comparativeindex 3734. The user can double click on the series type to toggle itbetween “Weekly” and “Daily.” The user can also double click on both thesolid and dashed selections to enter the desired period for the base andcomparison period graphs.

Next, a detailed description of the types of alerts that can be appliedby a user to customize the output is described below. The followingdescription will be better understood if read in conjunction with alertcontrols data 3506, shown in FIG. 38.

As previously stated, alerts can be set to establish criteria upon whicha report for web site 120 delivery customers can be sent by email uponthe triggering of an event defined by the alert. Two types of alerts arecommon: (1) a change measurement 3810 alert and (2) a gap measurement3812 alert. FIG. 31 illustrates an exemplary alert setting based onchange measurements from the prior period. The desired parameter to bechanged is change measurement 3810. Positioning the cursor within or inclose proximity to the word “Change” and right clicking using the mousecauses display arrow 1802 to appear. The area surrounding the word“Change” is now hot spot 1804. Hot spot 1804 is shown in phantom. Theuser can also position the cursor within hot spot 1804 and left clickthe mouse to cause control selection window 1806 to appear. Controlselection window 1806 provides a list of all of the selections of thedesired change measurement 3810 which can be chosen by the user. Changemeasurement 3810 parameters include: (1) Actual percent change 3814compared to prior period; (2) Percent of base change 3816 compared toprior period; and (3) Consistent rises or falls in a row 3818. The usercan select the desired change measurement 3810 by double clicking themouse on the desired selection and entering the amount desired. A titlefield for an alert name 3806 can be customized by user 3702 so that onreceipt of the alert email, user 3702 can immediately identify the alertsetting by name. Double clicking on “Enter Criteria” will update alertcontrols data 3506 and cause display arrow 1802 and control selectionwindow 1806 to disappear.

FIG. 32 illustrates an exemplary alert setting based on measurements ofgap 1708. As previously stated, gap is a measure of the amount ofvariation between the 9 period and the 21 period graphical results. Thedesired parameter to be changed is gap measurement 3812. Positioning thecursor within or in close proximity to the word “Gap” and right clickingusing the mouse causes display arrow 1802 to appear. The areasurrounding the word “Gap” is now hot spot 1804. Hot spot 1804 is shownin phantom. The user can also position the cursor within hot spot 1804and left click the mouse to cause control selection window 1806 toappear. Control selection window 1806 provides a list of all of theselections of the desired gap measurement 3812 which can be chosen bythe user. Gap measurement 3812 parameters include: (1) Current gap size3820; (2) Change compared to prior gap 3822; and (3) Consistent rises orfalls in a row 3824. User 3702 can select the desired gap measurement3812 by double clicking the mouse on the desired selection and enteringthe amount desired. A title field for alert name 3806 can be customizedby user 3702 so that on receipt of the alert email, user 3702 canimmediately identify the alert setting by name. Double clicking on“Enter Criteria” will update alert controls data 3506 and cause displayarrow 1802 and control selection window 1806 to disappear.

V. Environment

The present invention (i.e., aggregator 104, moving average generator108, user interface delivery module 116, or any part thereof) may beimplemented using hardware, software, or a combination thereof and maybe implemented in one or more computer systems or other processingsystems. In fact, in one embodiment, the invention is directed towardone or more computer systems capable of carrying out the functionalitydescribed herein. An example of a computer system 3300 is shown in FIG.33. The computer system 3300 includes one or more processors, such asprocessor 3303. The processor 3303 is connected to a communication bus3302. Various software embodiments are described in terms of thisexemplary computer system. After reading this description, it will beapparent to a person skilled in the relevant art how to implement theinvention using other computer systems and/or computer architectures.

Computer system 3300 also includes a main memory 3305, preferably randomaccess memory (RAM), and may also include a secondary memory 3310. Thesecondary memory 3310 may include, for example, a hard disk drive 3312and/or a removable storage drive 3314, representing a floppy disk drive,a magnetic tape drive, an optical disk drive, etc. The removable storagedrive 3314 reads from and/or writes to a removable storage unit 3318 ina well-known manner. Removable storage unit 3318, represents a floppydisk, magnetic tape, optical disk, etc., which is read by and written toby removable storage drive 3314. As will be appreciated, the removablestorage unit 3318 includes a computer usable storage medium havingstored therein computer software and/or data.

In alternative embodiments, secondary memory 3310 may include othersimilar means for allowing computer programs or other instructions to beloaded into computer system 3300. Such means may include, for example, aremovable storage unit 3322 and an interface 3320. Examples of such mayinclude a program cartridge and cartridge interface (such as that foundin video game devices), a removable memory chip (such as an EPROM, orPROM) and associated socket, and other removable storage units 3322 andinterfaces 3320 which allow software and data to be transferred from theremovable storage unit 3322 to computer system 3300.

Computer system 3300 may also include a communications interface 3324.Communications interface 3324 allows software and data to be transferredbetween computer system 3300 and external devices. Examples ofcommunications interface 3324 may include a modem, a network interface(such as an Ethernet card), a communications port, a PCMCIA slot andcard, etc. Software and data transferred via communications interface3324 are in the form of signals 3328 which may be electronic,electromagnetic, optical, or other signals capable of being received bycommunications interface 3324. These signals 3328 are provided tocommunications interface 3324 via a communications path (i.e., channel)3326. This channel 3326 carries signals 3328 and may be implementedusing wire or cable, fiber optics, a phone line, a cellular phone link,an RF link, and other communications channels.

In this document, the term “computer program product” refers toremovable storage units 3318, 3322, and signals 3328. These computerprogram products are means for providing software to computer system3300. The invention is directed to such computer program products.

Computer programs (also called computer control logic) are stored inmain memory 3305, and/or secondary memory 3310 and/or in computerprogram products. Computer programs may also be received viacommunications interface 3324. Such computer programs, when executed,enable the computer system 3300 to perform the features of the presentinvention as discussed herein. In particular, the computer programs,when executed, enable the processor 3303 to perform the features of thepresent invention. Accordingly, such computer programs representcontrollers of the computer system 3300.

In an embodiment where the invention is implemented using software, thesoftware may be stored in a computer program product and loaded intocomputer system 3300 using removable storage drive 3314, hard drive 3312or communications interface 3324. The control logic (software), whenexecuted by the processor 3303, causes the processor 3303 to perform thefunctions of the invention as described herein.

In another embodiment, the invention is implemented primarily inhardware using, for example, hardware components such as applicationspecific integrated circuits (ASICs). Implementation of the hardwarestate machine so as to perform the functions described herein will beapparent to persons skilled in the relevant art(s).

In yet another embodiment, the invention is implemented using acombination of both hardware and software.

VI. Conclusion

While various embodiments of the present invention have been describedabove, it should be understood that they have been presented by way ofexample only, and not limitation. It will be understood by those skilledin the art that various changes in form and details may be made thereinwithout departing from the spirit and scope of the invention as definedin the appended claims. Thus, the breadth and scope of the presentinvention should not be limited by any of the above-described exemplaryembodiments, but should be defined only in accordance with the followingclaims and their equivalents.

1. A computer implemented method for providing a stock purchase index,comprising the steps of: (1) receiving raw customer trading data; (2)segregating the raw customer trading data into buy and sell data; (3)sorting the buy and sell data to determine a total number of buyaccounts, a total number of sell accounts and a total number ofinvestors, wherein the total number of investors is determined by thetotal number of buy accounts plus the total number of sell accounts; (4)processing, using a processor, the sorted data to provide a stockpurchase index, wherein the stock purchase index is a sell simple index,wherein the sell simple index is the ratio of the total number of sellaccounts to the total number of investors, thereby providing ameasurement of investor selling participation; and (5) displaying, via auser display, the sell simple index in a stock purchase index report. 2.The computer implemented method of claim 1, wherein the sorting stepincludes determining and eliminating the buy and sell data related today traders.
 3. The computer implemented method of claim 1, wherein thedisplaying step includes displaying the stock purchase index report viaan email.
 4. The computer implemented method of claim 1, wherein thedisplaying step includes displaying the stock purchase index report viaa web site.
 5. The computer implemented method of claim 4, wherein thestep of displaying the stock purchase index report via the web sitecomprises the step of customizing the stock purchase index report usingcustomization information received from a user.
 6. The computerimplemented method of claim 5, wherein the step of customizing the stockpurchase index report includes providing a plurality of filters tocustomize the stock purchase index report.
 7. The computer implementedmethod of claim 5, wherein the step of customizing the stock purchaseindex report includes providing alerts to enable automatic emaildelivery upon the occurrence of a user-defined percentage change in thesell simple index from a prior period.
 8. The computer implementedmethod of claim 5, wherein the step of customizing the stock purchaseindex report includes providing alerts to enable automatic emaildelivery upon the occurrence of a user-defined percentage change in agap, wherein the gap is the difference between a first period series anda second period series.
 9. The computer implemented method of claim 1,wherein the processing step includes applying smoothing techniques tothe sell simple index to remove noise components.